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We consider the design of an array processor for space-time coded multi-antenna systems. As an alternative to the previously proposed zero-forcing method, in this paper, the maximum signal-to-noise ratio (SNR) criterion is used to obtain a balance between interference suppression and noise enhancement. Although the same in concept, this work differs from the conventional minimum mean-squared error method in that there is more than one desired signal dimension each corresponding to one of the space--time coded streams. It will be shown that the number of linear filters required by the maximum SNR array processor is no more than the dimension of the signal space or the number of collaborating transmit antennas. The advantages of this design are highly improved performance and reduced decoding complexity. Index Terms--Array processing, diversity, space-time codes.

Joint channel estimation and decoding in a time-varying Rayleigh fading channel is considered. Knowing that the optimal solution or even the truncated near-optimal solution using iterative processing has an exponential complexity which hinders the practicability, a reduced complexity approach is proposed. This approach keeps the existing channel estimation and decoding schemes almost intact, while applying iterative processing to effectively exchange information between them. Thus, the complexity is rendered linear, and estimator adaptability can be easily established. We apply this approach to pilot symbol-assisted modulation (PSAM) and differentially modulated systems. It turns out that the performance is improved and the robustness to fading parameters is enhanced. Through simulations, we also show that the proposed method performs almost as well as the near-optimal design. Index Terms--Channel estimation, iterative processing, multiple differential detection (MDD), pilot symbol-assisted modulation (PSAM), soft decoding.

In attempting to find a spectrally and power efficient channel code which is able to exploit maximum diversity from a wireless channel whenever available, we investigate the possibility of constructing a full antenna diversity space-time turbo code. As a result, both three-antenna and two-antenna (punctured) constructions are shown to be possible and very easy to find. To check the decodability and performance of the proposed codes, we derive nonbinary soil-decoding algorithms. The performance of these codes are then simulated and compared with two existing space-time convolutional codes (one has minimum worst-case symbol-error probability; the other has maximal minimum free distance) having similar decoding complexity. As the simulation results show, the proposed space-time turbo codes give similar or slightly better performance than the convolutional codes under extremely slow fading. When fading is fast, the better distance spectra of the turbo codes help seize the temporal diversity. Thus, the performance advantage of the turbo codes becomes evident. In particular, [10.sup.-5] bit-error rate and [10.sup.-3] frame-error rate can be achieved at less than 6-dB [E.sub.b]/[N.sub.0] with 1 b/s/Hz and binary phase-shift keying modulation. The practical issue of obtaining the critical channel state information (CSI) is also considered by applying an iteratively filtered pilot symbol-assisted modulation technique. The penalty when the CSI is not given a priori is about 2-3 dB. Index Terms--Channel estimation, multiple transmit antennas, space-time codes, turbo codes.

This paper considers noisy Wyner–Ziv coding (WZC), in which a remote noisy source is compressed with side information at the decoder only. The decoder side information is not limited to being Gaussian, thus this noisy WZC problem cannot be transformed into the conventional one tailored for noiseless sources. A new coding structure, named the residual-quantization (RQ) based noisy WZC, is proposed to solve the problem. This scheme explicitly constructs the theoretical auxiliary random variable to facilitate optimal reconstruction of the noisy source. In this two-stage encoder, the noisy source is quantized twice and the quantization error (residue) of the first stage is the input of the second stage. By sending only the quantization index of the second stage to the decoder, the corresponding code rate can theoretically approach the noisy WZC bound. Moreover, the RQ-based noisy WZC is implemented using graph-based codes. The main challenge is that it is necessary to design a codebook that is simultaneously good for source and channel coding for the first stage quantization, since this quantization code also acts as a channel code at the decoder. This problem is solved by constructing a low-density parity check (LDPC) code with edge degrees optimized for channel coding, and enhancing its performance for source coding by using a modified reinforced belief-propagation quantization algorithm. Simulation results show that the noisy Wyner-Ziv bounds can be practically approached by our implementation. In addition, the proposed implementation offers more flexibility in the code rates compared with the existing practical designs, making it more suitable for emerging applications such as fronthaul compression. [ABSTRACT FROM AUTHOR]

In this paper, we analytically study a random access network that uses the request-to-send and clear-to-send (RTS/CTS) handshake for reservation of transmission time. In the network, nodes initiate data transmission to a common base station (BS) by sending an RTS packet according to a transmission probability. The RTS packet of a node specifies the length of the node's requested data transmission interval, and will be successfully received by the BS if its signal to interference plus noise ratio (SINR) is higher than the capture ratio. The BS will then reply with a CTS packet to grant this node the requested data transmission interval and inform the other nodes not to interrupt. The transmission probabilities of RTS packets of all nodes will determine the average throughput and power consumption of each node. The set of all possible throughputs that can be achieved by the network is called the throughput region. We characterize the throughput region and provide an upper bound on the total transmission power consumption over the throughput region at the optimal operating point. Specifically, the upper bound corresponds to one of three points in the throughput region depending on the fraction of time occupied by the RTS packets. [ABSTRACT FROM PUBLISHER]

Linear-assignment Gel'fand-Pinsker coding (LA-GPC) is a coding technique for channels with interference known only at the transmitter, where the known interference is treated as side-information (SI). As a special case of the LA-GPC, dirty paper coding has been shown to be able to achieve the optimal interference-free rate for SI channels with perfect channel state information at the transmitter (CSIT). In the cases where only the channel distribution information at the transmitter (CDIT) is available, LA-GPC also has good (sometimes optimal) performance in a variety of fast and slow fading SI channels. In this letter, we design filters in the nested lattice based coding to make it achieve the same rate performance as the LA-GPC in multiple-input multiple-output (MIMO) channels. Compared with the random Gaussian codebooks used in previous works, our resultant coding schemes have algebraic structures and can be implemented in practical systems. Simulations in slow-fading channels are provided, and near interference-free error performance is obtained. The proposed coding schemes can serve as the fundamental building blocks to achieve the promised rate performance of MIMO Gaussian broadcast channels with CDIT or perfect CSIT. [ABSTRACT FROM AUTHOR]